PROTAC-mediated degradation reveals a non-catalytic function of AURORA-A kinase

Abstract

The mitotic kinase AURORA-A is essential for cell cycle progression and is considered a priority cancer target. Although the catalytic activity of AURORA-A is essential for its mitotic function, recent reports indicate an additional non-catalytic function, which is difficult to target by conventional small molecules. We therefore developed a series of chemical degraders (PROTACs) by connecting a clinical kinase inhibitor of AURORA-A to E3 ligase-binding molecules (for example, thalidomide). One degrader induced rapid, durable and highly specific degradation of AURORA-A. In addition, we found that the degrader complex was stabilized by cooperative binding between AURORA-A and CEREBLON. Degrader-mediated AURORA-A depletion caused an S-phase defect, which is not the cell cycle effect observed upon kinase inhibition, supporting an important non-catalytic function of AURORA-A during DNA replication. AURORA-A degradation induced rampant apoptosis in cancer cell lines and thus represents a versatile starting point for developing new therapeutics to counter AURORA-A function in cancer.

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Fig. 1: Bifunctional degrader molecules induce depletion of AURORA-A in cells.
Fig. 2: JB170 reduces AURORA-A levels by inducing proteolysis.
Fig. 3: JB170 is highly specific for AURORA-A.
Fig. 4: Protein-protein interactions between AURORA-A and CEREBLON support ternary complex formation.
Fig. 5: Degrader-mediated depletion and kinase inhibition of AURORA-A induce distinct cellular phenotypes.
Fig. 6: Degrader-mediated depletion of AURORA-A induces apoptosis in cancer cells.

Data availability

Sequence data have been deposited at GEO with accession no. GSE141911. SILAC MS proteomics data have been deposited at the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD017342. TMT MS proteomics data have been deposited with the dataset identifier PXD019585 (PRIDE). AURORA-A interactome data have been deposited with the dataset identifier PXD019684 (PRIDE). AURORA-A sedimentation profile in the presence and absence of RNases was obtained from http://r-deep.dkfz.de (AURKA_HUMAN.pdf). Source data are provided with this paper.

Code availability

Data analysis was mostly performed with published analysis tools (as described above). Custom code was only used for standard operations and will be made available by the corresponding authors on request.

References

  1. 1.

    Hanahan, D. & Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 144, 646–674 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Otto, T. & Sicinski, P. Cell cycle proteins as promising targets in cancer therapy. Nat. Rev. Cancer 17, 93–115 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Nigg, E. A. Mitotic kinases as regulators of cell division and its checkpoints. Nat. Rev. Mol. Cell Biol. 2, 21–32 (2001).

    CAS  PubMed  Google Scholar 

  4. 4.

    Marumoto, T., Zhang, D. & Saya, H. Aurora-A—a guardian of poles. Nat. Rev. Cancer 5, 42–50 (2005).

    CAS  PubMed  Google Scholar 

  5. 5.

    Kettenbach, A. N. et al. Quantitative phosphoproteomics identifies substrates and functional modules of Aurora and Polo-like kinase activities in mitotic cells. Sci. Signal 4, rs5 (2011).

    CAS  PubMed  Google Scholar 

  6. 6.

    Hochegger, H., Hegarat, N. & Pereira-Leal, J. B. Aurora at the pole and equator: overlapping functions of Aurora kinases in the mitotic spindle. Open Biol. 3, 120185 (2013).

    PubMed  PubMed Central  Google Scholar 

  7. 7.

    Tanner, M. M. et al. Frequent amplification of chromosomal region 20q12-q13 in ovarian cancer. Clin. Cancer Res. 6, 1833–1839 (2000).

    CAS  PubMed  Google Scholar 

  8. 8.

    Bischoff, J. R. et al. A homologue of Drosophila aurora kinase is oncogenic and amplified in human colorectal cancers. EMBO J. 17, 3052–3065 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Zhou, H. et al. Tumour amplified kinase STK15/BTAK induces centrosome amplification, aneuploidy and transformation. Nat. Genet. 20, 189–193 (1998).

    CAS  PubMed  Google Scholar 

  10. 10.

    Wang, X. et al. Overexpression of aurora kinase A in mouse mammary epithelium induces genetic instability preceding mammary tumor formation. Oncogene 25, 7148–7158 (2006).

    CAS  PubMed  Google Scholar 

  11. 11.

    Treekitkarnmongkol, W. et al. Aurora kinase-A overexpression in mouse mammary epithelium induces mammary adenocarcinomas harboring genetic alterations shared with human breast cancer. Carcinogenesis 37, 1180–1189 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Gong, X. et al. Aurora a kinase inhibition is synthetic lethal with loss of the RB1 tumor suppressor gene. Cancer Discov. 9, 248–263 (2019).

    CAS  PubMed  Google Scholar 

  13. 13.

    Wu, C. et al. Targeting AURKA-CDC25C axis to induce synthetic lethality in ARID1A-deficient colorectal cancer cells. Nat. Commun. 9, 3212 (2018).

    PubMed  PubMed Central  Google Scholar 

  14. 14.

    Mollaoglu, G. et al. MYC drives progression of small cell lung cancer to a variant neuroendocrine subtype with vulnerability to aurora kinase inhibition. Cancer Cell 31, 270–285 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Otto, T. et al. Stabilization of N-Myc is a critical function of Aurora A in human neuroblastoma. Cancer Cell 15, 67–78 (2009).

    CAS  PubMed  Google Scholar 

  16. 16.

    Borisa, A. C. & Bhatt, H. G. A comprehensive review on Aurora kinase: small molecule inhibitors and clinical trial studies. Eur. J. Med. Chem. 140, 1–19 (2017).

    CAS  PubMed  Google Scholar 

  17. 17.

    Gorgun, G. et al. A novel Aurora-A kinase inhibitor MLN8237 induces cytotoxicity and cell-cycle arrest in multiple myeloma. Blood 115, 5202–5213 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. 18.

    O’Connor, O. A. et al. Randomized phase III study of alisertib or investigator’s choice (Selected Single Agent) in patients with relapsed or refractory peripheral T-cell lymphoma. J. Clin. Oncol. 37, 613–623 (2019).

    PubMed  PubMed Central  Google Scholar 

  19. 19.

    DuBois, S. G. et al. Phase II trial of alisertib in combination with irinotecan and temozolomide for patients with relapsed or refractory neuroblastoma. Clin. Cancer Res. 24, 6142–6149 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Mosse, Y. P. et al. A Phase II study of alisertib in children with recurrent/refractory solid tumors or leukemia: children’s oncology group Phase I and pilot consortium (ADVL0921). Clin. Cancer Res. 25, 3229–3238 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Beltran, H. et al. A Phase II trial of the Aurora kinase A inhibitor alisertib for patients with castration-resistant and neuroendocrine prostate cancer: efficacy and biomarkers. Clin. Cancer Res. 25, 43–51 (2019).

    CAS  PubMed  Google Scholar 

  22. 22.

    Brockmann, M. et al. Small molecule inhibitors of Aurora-A induce proteasomal degradation of N-myc in childhood neuroblastoma. Cancer Cell 24, 75–89 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Dauch, D. et al. A MYC-Aurora kinase A protein complex represents an actionable drug target in p53-altered liver cancer. Nat. Med. 22, 744–753 (2016).

    CAS  PubMed  Google Scholar 

  24. 24.

    Toya, M., Terasawa, M., Nagata, K., Iida, Y. & Sugimoto, A. A kinase-independent role for Aurora A in the assembly of mitotic spindle microtubules in Caenorhabditis elegans embryos. Nat. Cell Biol. 13, 708–714 (2011).

    PubMed  Google Scholar 

  25. 25.

    Zheng, F. et al. Nuclear AURKA acquires kinase-independent transactivating function to enhance breast cancer stem cell phenotype. Nat. Commun. 7, 10180 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Richards, M. W. et al. Structural basis of N-Myc binding by Aurora-A and its destabilization by kinase inhibitors. Proc. Natl Acad. Sci. USA 113, 13726–13731 (2016).

    CAS  PubMed  Google Scholar 

  27. 27.

    Gustafson, W. C. et al. Drugging MYCN through an allosteric transition in Aurora kinase A. Cancer Cell 26, 414–427 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Burslem, G. M. & Crews, C. M. Proteolysis-targeting chimeras as therapeutics and tools for biological discovery. Cell 181, 102–114 (2020).

    CAS  PubMed  Google Scholar 

  29. 29.

    Hanzl, A. & Winter, G. E. Targeted protein degradation: current and future challenges. Curr. Opin. Chem. Biol. 56, 35–41 (2020).

    CAS  PubMed  Google Scholar 

  30. 30.

    Winter, G. E. et al. Phthalimide conjugation as a strategy for in vivo target protein degradation. Science 348, 1376–1381 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Bondeson, D. P. et al. Catalytic in vivo protein knockdown by small-molecule PROTACs. Nat. Chem. Biol. 11, 611–617 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Maniaci, C. & Ciulli, A. Bifunctional chemical probes inducing protein-protein interactions. Curr. Opin. Chem. Biol. 52, 145–156 (2019).

    CAS  PubMed  Google Scholar 

  33. 33.

    Sloane, D. A. et al. Drug-resistant Aurora A mutants for cellular target validation of the small molecule kinase inhibitors MLN8054 and MLN8237. ACS Chem. Biol. 5, 563–576 (2010).

    CAS  PubMed  Google Scholar 

  34. 34.

    Dodson, C. A. et al. Crystal structure of an Aurora-A mutant that mimics Aurora-B bound to MLN8054: insights into selectivity and drug design. Biochem. J. 427, 19–28 (2010).

    CAS  PubMed  Google Scholar 

  35. 35.

    Douglass, E. F. Jr, Miller, C. J., Sparer, G., Shapiro, H. & Spiegel, D. A. A comprehensive mathematical model for three-body binding equilibria. J. Am. Chem. Soc. 135, 6092–6099 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. 36.

    Crosio, C. et al. Mitotic phosphorylation of histone H3: spatio-temporal regulation by mammalian Aurora kinases. Mol. Cell Biol. 22, 874–885 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Meraldi, P. & Nigg, E. A. Centrosome cohesion is regulated by a balance of kinase and phosphatase activities. J. Cell Sci. 114, 3749–3757 (2001).

    CAS  PubMed  Google Scholar 

  38. 38.

    Klaeger, S. et al. The target landscape of clinical kinase drugs. Science 358, eaan4368 (2017).

    PubMed  PubMed Central  Google Scholar 

  39. 39.

    Chamberlain, P. P. et al. Structure of the human Cereblon-DDB1-lenalidomide complex reveals basis for responsiveness to thalidomide analogs. Nat. Struct. Mol. Biol. 21, 803–809 (2014).

    CAS  PubMed  Google Scholar 

  40. 40.

    Farnaby, W. et al. BAF complex vulnerabilities in cancer demonstrated via structure-based PROTAC design. Nat. Chem. Biol. 15, 672–680 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Gadd, M. S. et al. Structural basis of PROTAC cooperative recognition for selective protein degradation. Nat. Chem. Biol. 13, 514–521 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Zengerle, M., Chan, K. H. & Ciulli, A. Selective small molecule induced degradation of the BET bromodomain protein BRD4. ACS Chem. Biol. 10, 1770–1777 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Elkins, J. M., Santaguida, S., Musacchio, A. & Knapp, S. Crystal structure of human Aurora B in complex with INCENP and VX-680. J. Med. Chem. 55, 7841–7848 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Tsuchiya, Y. et al. Covalent Aurora A regulation by the metabolic integrator coenzyme A. Redox Biol. 28, 101318 (2020).

    CAS  PubMed  Google Scholar 

  45. 45.

    Buchel, G. et al. Association with Aurora-A controls N-MYC-dependent promoter escape and pause release of RNA polymerase II during the cell cycle. Cell Rep. 21, 3483–3497 (2017).

    PubMed  PubMed Central  Google Scholar 

  46. 46.

    Caudron-Herger, M. et al. R-DeeP: proteome-wide and quantitative identification of RNA-dependent proteins by density gradient ultracentrifugation. Mol. Cell 75, 184–199 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Bondeson, D. P. et al. Lessons in PROTAC design from selective degradation with a promiscuous warhead. Cell Chem. Biol. 25, 78–87 (2018).

    CAS  PubMed  Google Scholar 

  48. 48.

    Remillard, D. et al. Degradation of the BAF Complex Factor BRD9 by heterobifunctional ligands. Angew. Chem. Int. Ed. 56, 5738–5743 (2017).

    CAS  Google Scholar 

  49. 49.

    Baluapuri, A. et al. MYC Recruits SPT5 to RNA Polymerase II to promote processive transcription elongation. Mol. Cell 74, 674–687 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. 51.

    Zecha, J. et al. TMT labeling for the masses: a robust and cost-efficient, in-solution labeling approach. Mol. Cell Proteom. 18, 1468–1478 (2019).

    CAS  Google Scholar 

  52. 52.

    Bian, Y. et al. Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC-MS/MS. Nat. Commun. 11, 157 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Cox, J. et al. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 10, 1794–1805 (2011).

    CAS  PubMed  Google Scholar 

  54. 54.

    Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55.

    Medard, G. et al. Optimized chemical proteomics assay for kinase inhibitor profiling. J. Proteome Res. 14, 1574–1586 (2015).

    CAS  PubMed  Google Scholar 

  56. 56.

    Cox, J. et al. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol. Cell Proteom. 13, 2513–2526 (2014).

    CAS  Google Scholar 

  57. 57.

    Fedorov, O., Niesen, F. H. & Knapp, S. Kinase inhibitor selectivity profiling using differential scanning fluorimetry. Methods Mol. Biol. 795, 109–118 (2012).

    CAS  PubMed  Google Scholar 

  58. 58.

    Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank A. Kutschke for excellent technical assistance. Manuscript editing was provided by V. Matarese. We appreciate the scientific discussions with M. Eilers and K. Burger about the biology of AURORA-A and DICER1 and thank the Eilers laboratory for cell lines and plasmids. This work was supported by grants from the German Research Foundation (WO 2108/1-1 to E.W., GRK 2243 to C.S.), the European Research Council (TarMYC to E.W.) and the Federal Ministry of Education and Research (CANCER to E.W. and S.K.). S.M. and M.S. are grateful for support by the SGC, a registered charity (no. 1097737) that receives funds from AbbVie, Bayer Pharma AG, Boehringer Ingelheim, Canada Foundation for Innovation, Eshelman Institute for Innovation, Genome Canada, Innovative Medicines Initiative (EU/EFPIA) (EUbOPEN, agreement no. 875510), Janssen, Merck KGaA, MSD, Ontario Ministry of Economic Development and Innovation, Pfizer, São Paulo Research Foundation-FAPESP, Takeda and the Wellcome Trust. M.W. is grateful for support by the Else Kröner-Fresenius PhD program (TRIP) and J.B. by the German Cancer Research Center DKTK.

Author information

Affiliations

Authors

Contributions

J.B. synthesized all degrader molecules and B.A. performed most of the cell-based experiments. M.S. performed BRET and calorimetry assays, M.W. synthesized E3 ligands and linkers. M.D. performed all computational modeling. J.D.S., J.H., A.N., M.V., N.D.S., L.E., A.B. and P.B. contributed experimental data. L.S. expressed recombinant proteins. A.S., S.H. and B.K. performed and analyzed MS experiments together with B.A. and J.H. S.H. and B.K. analyzed alisertib and JB170 protein binding. C.S. supervised computational modeling studies. S.K. supervised the synthesis and biophysical experiments, and E.W. supervised the cell-based assays. S.K. and E.W. designed the study and wrote the manuscript with the help of all authors.

Corresponding authors

Correspondence to Stefan Knapp or Elmar Wolf.

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Competing interests

B.K. is a cofounder and shareholder of msAId GmbH and OmicScouts GmbH. B.K. has no operational role in either company. The University of Würzburg has filed a patent for the degraders described in the study and E.W. is listed as an inventor.

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Extended data

Extended Data Fig. 1 Related to Fig. 1.

a, Model of bifunctional degrader molecules (PROTACs) of AURORA-A. b, Ribbon model of AURORA-A and structural formula of alisertib. The structure of AURORA-A bound to MLN8054 (PDB: 2X81)33 identified a solvent-exposed carboxyl group on the compound to which linkers could be attached by amide bonds. c, Degrader and ligand structures and their effects on AURORA-A-NanoLuc target engagement. HEK293 cells transfected with an AURORA-A-NanoLuc fusion construct were incubated with various concentrations of the AURORA-A degrader molecules or their components together with an energy transfer probe for 2 h and luminescence was measured. EC50 values were calculated by assuming a sigmoidal dose–response relationship (four parameters). The graph shows one of the two biological replicates. The graphs display the profile of each compound for the assay as shown in Fig. 1a. d, Bar diagram showing the binding of degrader molecules to AURORA-A. AURORA-A was incubated with degrader molecules and binding was analyzed by thermal shift assays and compared to alisertib. Pomalidomide and VHL-binding moieties were used as controls. Bars represent mean ± s.d. for n = 4 replicates (n = 3 for JB161) e, Immunoblot of AURORA-A. AURORA-A and AURORA-B were depleted in IMR5 cells by siRNA and AURORA-A levels were compared to cells treated with JB170 (1 µM) or alisertib (1 µM) and to control cells (Ctr). f, Immunoblot of AURORA-A. MV4–11 cells were treated with 0.1 µM JB170 for the indicated times and AURORA-A levels were compared to control cells. g, Immunoblot of AURORA-A. MV4–11 cells were treated with 0.1 µM JB158 for the indicated times, and AURORA-A levels were compared to control cells. Source data

Extended Data Fig. 2 Related to Fig. 2.

a, Immunoblot of AURORA-A. MV4–11 cells were treated with various concentrations of JB170 and alisertib for 6 h, and AURORA-A levels were compared to control cells. b, Immunoblot of AURORA-A. MV4–11 cells were treated with various concentrations of JB158 and alisertib for 6 h and AURORA-A levels were compared to control cells. c, Immunoblot of AURORA-A and bar diagram of quantitative rtPCR analysis. RNA and protein were isolated from MV4–11 cells treated with JB170 (0.1 μM) and alisertib (0.1 μM) for 6 and 24 h. AURORA-A protein (top) and RNA levels (bottom) were analyzed. Short and long exposures are shown for AURORA-A. AURORA-A expression levels were normalized to control cells (DMSO). Bars represent mean of technical replicates. d, Immunoblot of AURORA-A and bar diagram of quantitative rtPCR analysis. RNA and protein were isolated from MV4–11 cells treated with JB158 (0.1 µM) or alisertib (0.1 µM) for 6 h. AURORA-A protein (top) and RNA levels (bottom) were analyzed. Vinculin was used as a loading control. The AURORA-A expression levels are normalized to control cells (DMSO). Bars represent mean of technical replicates. e, Bar diagram of quantitative rtPCR analysis. RNA was isolated from IMR5 cells treated with an siRNA against AURORA-A, a non-targeting control (siCtr), JB170 and control cells (DMSO). AURORA-A RNA levels were analyzed by RT-qPCR in comparison to beta-2 microglobulin and normalized to control cells (siCtr). Bars represent mean ± s.e.m. of relative expression for n = 3 biological replicates. f, Immunoblot of AURORA-A upon washout of JB170. MV4–11 cells were treated with JB170 (0.1 µM) for 3 h before they were either cultured in JB170-containing or JB170-free medium for up to 6 h. g, Immunoblot of AURORA-A. MV4–11 cells were treated with different concentrations JB170 and alisertib for 6 h and compared to cells treated with one compound or untreated cells. h, Immunoblot of AURORA-A. MV4–11 cells were treated for 6 h with JB170 (0.1 µM) and unconjugated thalidomide (+: 1 µM, ++: 10 µM, +++: 20 µM). i, Structure of JB211 that is an inactive analog of JB170. j, Immunoblot of AURORA-A. MV4–11 cells were treated with JB170 (0.1 µM) and proteasomal inhibitor MG132 (10 µM) for 6 h. k, Immunoblot of AURORA-A. MV4–11 cells were treated with different concentrations JB170 and the NEDD8-activating enzyme (NAE) inhibitor MLN4924 (3 µM) for 6 h. l, Immunoblot of AURORA-A. MV4–11 cells were treated with different concentrations JB158 and the NEDD8-activating enzyme inhibitor MLN4924 (3 µM) for 6 h. m, Immunoblot of HA-tagged AURORA-A. Kinase-dead versions of HA-tagged AURORA-A (AURORA-AK162R, AURORA-AD274N) and the HA-tagged wild-type protein (WT) were expressed in IMR5 cells. Cells were then treated with alisertib (1 µM) and JB170 (1 µM) for 18 h, and AURORA-A levels were analyzed using an anti-HA tag antibody and an anti-AURORA-A antibody. n, Immunoblot of HA-tagged AURORA-A. Kinase-dead version of HA-tagged AURORA-A, AURORA-AK162R and the HA-tagged wild-type protein (WT) were expressed in MV4–11 cells. Cells were then treated with alisertib (1 µM) or JB170 (1 µM) for 18 h, and AURORA-A levels were analyzed with an anti-HA tag antibody and an anti-AURORA-A antibody o, Immunoblot of AURORA-A. U2OS cells were treated with different concentrations of JB170 for 6 h. p, Immunoblot of AURORA-A. HLE cells were treated with different concentrations of JB170 for 6 h. q, Immunoblot of AURORA-A. HLE cells were treated with JB158 (1 µM) for the indicated time periods. r, Immunoblot of AURORA-A. U2OS cells were treated with different concentrations of JB158 for 6 h. s, Immunoblot of AURORA-A. HLE cells were treated with different concentrations of JB158 for 6 h. Source data

Extended Data Fig. 3 Related to Fig. 3.

a, Effects of ligands and degraders on AURORA-B-NanoLuc target engagement. HEK293 cells transfected with an AURORA-B-NanoLuc fusion construct were incubated with various concentrations of the AURORA-A degraders or their components together with an energy transfer probe for 2 h and luminescence was measured. EC50 values were calculated by assuming a sigmoidal dose–response relationship (four parameters). The graph shows one of the two biological replicates. b, Immunoblot of AURORA-B. AURORA-A and AURORA-B were depleted in IMR5 cells by siRNA and AURORA-B levels were compared to cells treated with JB170 (1 µM) or alisertib (1 µM) and to control cells (Ctr). c, Immunoblot of AURORA-A and AURORA-B. MV4–11 cells were treated with various concentrations of JB170 and alisertib for 24 h, and protein levels were compared to control cells. d, Immunoblot of AURORA-A and AURORA-B. IMR5 cells were treated with DMSO, JB170 or alisertib for 6 h and protein levels were compared. e, Immunoblot of AURORA-A, GSPT and IKZF1. MV4–11 cells were treated with JB170, alisertib, pomalidomide (Pom.) and thalidomide (Thal.) for 18 h. f, g, Volcano plot showing changes in protein abundance. IMR5 cells were treated with JB170 (1 μM) or alisertib (1 μM) for 6 h and proteins were analyzed by isobaric labeling (TMT: tandem mass tag) followed by mass spectrometry. The X-axis displays the relative abundance of all identified proteins (6485) in JB170-treated vs. alisertib-treated cells (log2FC). The Y-axis displays the p-value (-log10) from replicate experiments (Student’s t-test, two-sided, permutation-based FDR correction, FDR: 5%). AURORA-A and other alisertib-binding proteins (f) or neosubstrates of CEREBLON (g) are labeled (orange). h, Volcano plot showing changes in protein abundance. IMR5 cells were treated with JB170 (1 µM) or JB211 (1 µM) for 6 h, and proteins were analyzed by isobaric labeling (TMT: tandem mass tag) followed by mass spectrometry. The X-axis displays the relative abundance of all identified proteins (6485) in JB170-treated vs. JB211-treated cells (log2FC). The Y-axis displays the p-value (-log10) from triplicate experiments (Student’s t-test, two-sided, permutation-based FDR correction, FDR: 5%). AURORA-A, other alisertib-binding proteins and protein kinases are labeled. Source data

Extended Data Fig. 4 Related to Fig. 4.

a, Model of the AURORA-A (blue) / CEREBLON (purple) complex. Structures of AURORA-A with alisertib and of CEREBLON with lenalidomide39 were used for protein-protein docking. The top-ranking solution is displayed (ACc1: AURORA-A-CEREBLON complex 1). Alisertib and lenalidomide are shown in green and aqua, respectively. b, Model of the second-best AURORA-A (blue)-CEREBLON (purple) complex compatible with JB170 binding (ACc2). Structures of AURORA-A with alisertib and of CEREBLON with lenalidomide were used for protein-protein docking. Alisertib and lenalidomide are shown in green and aqua, respectively. c, Modeled ternary complex structure of JB170 (orange) bound to the ACc1 shown in Extended Data Fig. 4a. Alisertib (green) and lenalidomide (aqua) were modified, connected and minimized to give JB170. d, Modeled ternary complex of JB170 (orange) bound to the ACc2 shown in Extended Data Fig. 4b. Alisertib (green) and lenalidomide (aqua) were modified, connected and minimized to give JB170. e, Docking solutions of the active degraders JB170 and JB158 as well as the less functional degraders JB159, JB169, JB171 and negative control JB211 in the AURORA-A (blue)-CEREBLON (purple) complexes ACc1 and ACc2. Scaffolds of thalidomide and alisertib used as light constraints during docking and as reference structures for the substructure root-mean-square deviation of atomic positions (RMSD) measurements are shown. Active degraders (labeled in green) achieve RMSD values below 1 Å with respect to both alisertib and the thalidomide scaffold. f, Immunoblots of immunoprecipitation experiments. Cells expressing HA-tagged wild-type AURORA-A (WT), a version of AURORA-A (AURORA-AImut) with 12 amino acid substitutions (R137E, K153E, K156E, F157E, I158E, R189E, P191W, K224E, E239R, S266W, A267W and R375E) or an empty vector (Ctr) were treated with 0.5 µM JB170 for 6 h. AURORA-A was precipitated with an anti-HA tag antibody, and the amount of co-precipitated CEREBLON was tested by immunoblotting. g, AURORA-A levels based on luciferase measurements. Wild-type (WT) or AURORA-A with one amino acid substitution (AURORA-AP191W) were fused to luciferase fragment (HiBiT) and expressed in MV4–11 cells. Cells were treated with 1 µM alisertib for 6 h, lysed, complemented with the second luciferase fragment (largeBiT), and measured for luciferase activity. Bars represent mean ± s.d. of n = 3 replicates. Source data

Extended Data Fig. 5 Related to Fig. 4.

a, Isothermal titration calorimetry experiments of AURORA-A into TBD (left panel, no measurable binding was observed), the binary complexes of AURORA-A/JB170, CEREBLON(TBD)/JB170 and ternary complex of AURORA-A/CEREBLON(TBD)/JB170. Shown are the raw heat rates on the top panel with integrated, baseline-corrected heats per injection and the corresponding fits below. An overlay of all curves (merged) is shown on the bottom left. b, Immunoblots of immunoprecipitation experiments. AURORA-A was precipitated with an anti-HA tag antibody from MV4–11 cells stably expressing HA-tagged AURORA-A or control cells transduced with an empty vector after treatment with 0.5 µM JB170 or 5 µM thalidomide (Thal.). The amount of co-precipitated CEREBLON and VHL was tested by immunoblotting. c, Immunoblots of immunoprecipitation experiments. AURORA-A was precipitated with an anti-HA tag antibody from MV4–11 cells stably expressing HA-tagged AURORA-A ( + ) or from control cells (-) after treatment with CEREBLON-based degraders (JB170, JB171, JB211), VHL-based degraders (JB160, JB161) or DMSO. The amount of co-precipitated CEREBLON and VHL was tested by immunoblotting. d, Immunoblots of immunoprecipitation experiments. BRD4 was precipitated with a specific antibody from MV4–11 cells after treatment with the VHL-based PROTAC MZ1 or DMSO in the presence of 5 mM MG132 for 1 h. The amount of co-precipitated VHL was tested by immunoblotting. e, Structural superposition of AURORA-A (blue, with bound alisertib in green) and AURORA-B. Residues with a maximum distance of 5 Å from CEREBLON in the AURORA-A-CEREBLON complex models are shown in cyan. Non-conserved amino acids near the proposed interaction interfaces of AURORA-A with CEREBLON are highlighted as labeled sticks and provided as a tabular list below the figure. Source data

Extended Data Fig. 6 Related to Fig. 5.

a, Histogram of BrdU incorporation. The amount of incorporated BrdU is shown for cells in the S-phase in Fig. 5a. b, Histogram of BrdU incorporation. The amount of incorporated BrdU is shown for cells in the S-phase in Fig. 5e. c, Immunoblot of AURORA-A. IMR5 cells overexpressing HA-tagged AURORA-A upon incubation with doxycycline (Dox) or control cells (EtOH) were treated with JB170 (1 µM) or alisertib (1 µM) for 18 h. d, Flow cytometry plots showing cell cycle distribution. IMR5 cells overexpressing AURORA-A upon incubation with doxycycline (Dox) or control cells (EtOH, as shown in Extended Data Fig. 6c) were treated with JB170 (1 µM) or alisertib (1 µM) for 18 h. Cells were labeled with BrdU, stained with PI, and analyzed by flow cytometry. The amount of intercalating PI (top) and the correlation of BrdU to PI (bottom) are shown. e, Histogram showing BrdU incorporation for cells in the S-phase in Extended Data Fig. 6d. f, Immunoblot of AURORA-A. AURORA-A was depleted in IMR5 cells by an siRNA and AURORA-A levels were analyzed by immunoblotting for biological triplicates. Cells were analyzed by flow cytometry as shown in Extended Data Fig. 6g,h. g, Cell cycle distribution analyzed by flow cytometry. IMR5 cells depleted for AURORA-A by siRNA were labeled with BrdU, stained with PI, and analyzed by flow cytometry. The amount of intercalating PI (top) and the correlation of BrdU to PI (bottom) are shown. h, Histogram showing BrdU incorporation for cells in the S-phase in Extended Data Fig. 6g and two additional biological replicates. i, Scatter plot of the AURORA-A interactome. The X-axis displays the enrichment (log2FC) of proteins in HA-AURORA-A-expressing cells compared to control cells (Ctr). The Y-axis displays the protein intensities (log10). Substrates of AURORA-A5 are labeled. j, Immunoblots of HA-tagged AURORA-A and DICER1. HA-precipitations were performed from HEK293 cells transfected to express versions of HA-tagged catalytically inactive AURORA-A (AURORA-AD274N, AURORA-AK162R) or the wild-type protein. Exogenous AURORA-A was detected with an anti-HA tag antibody, and levels of DICER1 were analyzed in the input and immunoprecipitant by antibodies recognizing the endogenous protein. Control cells (Ctr) did not express HA-tagged protein. k, AURORA-A sedimentation profile in the presence and absence of RNases. The graph is a re-analysis of published data46 retrieved from http://r-deep.dkfz.de/. Source data

Extended Data Fig. 7 Related to Fig. 6.

a, b, Cell death assay. IMR5 cells expressing AURORA-AT217D upon incubation with doxycycline (Dox) or control cells (EtOH) were treated with JB170 (0.5 μM, low; 1 μM, high) or JB211 (0.5 μM, low; 1 μM, high) for 72 h. Cells were stained with annexin (a) and PI (b), and apoptotic cells were counted by flow cytometry. c, Fractions of apoptotic cells analyzed by flow cytometry. IMR5 cells expressing AURORA-AT217D upon incubation with doxycycline (Dox) or control cells (EtOH) were treated with JB170 (1 µM) for indicated times. Cells were stained with annexin and PI, and apoptotic cells were counted by flow cytometry (50,000 sorted events) (d) Bar diagram showing cellular viability. IMR5 cells expressing AURORA-AT217D upon incubation with doxycycline (Dox) or control cells (EtOH) were treated with 0.5 µM and 1 µM JB170 or JB211 for 72 h, and cellular viability was measured by the alamarBlue assay. Bars represent mean ± s.d. of n = 3 replicate experiments. P-values were calculated with two-tailed unpaired t-test assuming equal variance.

Extended Data Fig. 8 Visualization of the flow cytometry gating.

a, FACS gating strategy for cell cycle distribution (BrdU-PI flow cytometry). The gating strategy is shown for one exemplary experiment. b, FACS gating strategy for the analysis of annexin-positive cells.

Supplementary information

Supplementary Information

Supplementary Notes 1 and 2.

Reporting Summary

Supplementary Table 1

EC50 values of AURORA-A- and AURORA-B-NanoLuc target engagement assay. EC50 values were calculated by assuming a sigmoidal dose–response relationship (four parameters). Values are mean ± s.e.m calculated from n = 2 biological replicates of which one is shown in Extended Data Fig. 1c for AURORA-A and Extended Data Fig. 3a for AURORA-B.

Supplementary Table 2

Reagents and sequences.

Supplementary Data 1

Kinobead selectivity profiling of alisertib and JB170 in MV4–11 cell lysates.

Supplementary Data 2

Proteomics analysis of relative protein abundance in MV4–11 cells by SILAC labeling.

Supplementary Data 3

Proteomics analysis of relative protein abundance in IMR5 cells by TMT labeling.

Supplementary Data 4

AURORA-A-interacting proteins.

Source data

Source Data Fig. 1

Uncropped immunoblots for Fig. 1.

Source Data Fig. 2

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Source Data Fig. 4

Uncropped immunoblots for Fig. 4.

Source Data Fig. 5

Uncropped immunoblots for Fig. 5.

Source Data Extended Data Fig. 1

Uncropped immunoblots for Extended Data Fig. 1.

Source Data Extended Data Fig. 2

Uncropped immunoblots for Extended Data Fig. 2.

Source Data Extended Data Fig. 3

Uncropped immunoblots for Extended Data Fig. 3.

Source Data Extended Data Fig. 4

Uncropped immunoblots for Extended Data Fig. 4.

Source Data Extended Data Fig. 5

Uncropped immunoblots for Extended Data Fig. 5.

Source Data Extended Data Fig. 6

Uncropped immunoblots for Extended Data Fig. 6.

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Adhikari, B., Bozilovic, J., Diebold, M. et al. PROTAC-mediated degradation reveals a non-catalytic function of AURORA-A kinase. Nat Chem Biol 16, 1179–1188 (2020). https://doi.org/10.1038/s41589-020-00652-y

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